This invention relates to combinations of segmentations, and in particular to clustering based combination of multiple segmentations of images, more particularly images of handwritten or printed text.
Segmentation, and in particular, segmentation of image data, can be a difficult problem. For example, segmentation of scanned handwritten or printed documents into lines of text is a first stage upon which first interpretation of the text may be based. Therefore, errors in such segmentation into lines can lead to significant errors in automated text recognition. Approaches that defer line segmentation decisions can be substantially more complex.
Segmentation of images has many other important applications, for example, in processing of biological images. Furthermore, segmentation of other types of elements in a data representation is an important part of many types of analyses other than for image data. For example, segmentation of sets of individuals into groups is important in many personalization systems.
In many applications, a variety of segmentation tools or procedures are available, each with different characteristics. For example, one tool may provide high accuracy for one class of inputs, while another tool may provide high accuracy for another class of inputs.